1. Web-based DHIS Daily Capturing (DDC)
Strategy for improving Data Quality at Service Point Level

2. TABLE OF CONTENT
Project Rationale
Legislation, Policies and SOPs
Business Process Prior WebDCC
Business Process after WebDCC
Principles of webDHISDDC

3. 5 webDHIS Transition Phases
Project Rationale
Reduce Audit Findings
Improve Timely Access to Data
Rationalisation of Registers
By improving Data Quality and Integrity
Strengthen Information Management
Promote EBD Making
Reduce Multiple Data Collection tools .
The Auditor General (AG) bi-annual audit main finding relates to the reliability of data = discrepancies between registers and monthly input forms.
DDC is one of the strategies NDOH embarked on to improve data quality and audit outcomes
Establish Building Block of NHI

4. Legislation, Policies, Strategies, Norms & Standards
The WebDHIS eHealth Project conforms with all applicable legislative frameworks,. The include:
The National Health Act 2nd Version;
The District Health Management Information System (DHMIS) Policy 2011;
The Medium Term Strategic Framework (MTSF) 2014 – 2019;
National Development Plan 2030;
eHealth Strategy for South Africa 2014 – 2019;
National Health Normative Standards Framework for Interoperability in eHealth in South Africa (version 2.0, March 2014);
White Paper - National Health Insurance for South Africa (Version 40, 11 December 2015)

5. Business Process prior webDHISDDC
RESOURCES
SKILLS
&
TIME
Patient record
Step 1
Doctor or nurse interacts with patient
No patient record, Incomplete, illegible, undated data
Multiplicity of data collection tools, duplication
non-standardised
Step 2
Sub-set of data recorded in Tick Register
Inability to collate data accurately
Step 3
Weekly & monthly summary report compiled (manual calculation)
Inability to collate data accurately
Step 4
Monthly summaries collated (manual calculation)
In this slide we look at the challenges we face to improve data quality. It describes the current steps followed in the information cycle and highlights the challenges experiences during each step
Data capture errors
Incorrect data elements activated
Validation not done
Step 5
Monthly data capture into webDHIS
mostly sub-district level
No feedback
Little data analysis and use by program managers
Step 6
Data analysis and feedback

6. Business Process after WebDHISDDC
Data entered
Patient clinical records standardise – verify data & rapid internal audits
Step 1
Doctor or nurse interacts with patient
Patient record
Register rationalisation
Less & specific elements per consulting room – reduce human error
Step 2
Sub-set of data recorded in Tick Register
Reduces manual calculation time
Internal aggregation reduces human error
Step 3
Monthly summary report compiled
Step 4
Monthly summaries collated
In this slide we propose a new approach that can address the challenges identified at each step in the previous slide.
Errors can be identified and corrected with clinicians daily
Capture & validate DAILY totals into WebDHIS by consulting room (subset)
Capture & validate MONTHLY totals by facility (subset)
Step 5
Less time on validation & verification = more time for analysis, feedback & use
Step 6
Data analysis, feedback and use

7. Principles of Daily Data Capturing
DATA CLERK OM
CLINICIAN
PATIENT
CAPTURE & VALIDATE
CONSULTATION
VERIFICATION
REGISTRATION AND DATA CAPTURERS ROOM
RECORD SERVICES OFFERED
SIGNED OFF
BULK FILLING CABINETS
Walkthrough in the facility to do assessment of patient flow, service points and services rendered at each point
All patients start at reception for registration and collection of their files before consultation
PHC headcount to be collected at the Reception as stated on the (DHMIS Policy) Facility SOP.
Daily data is captured from the registers in each service point to Web-based DHIS
Computer with Internet access.
Facility staff have been trained on web-DHIS
Data capturer or other computer-literate staff member to capture daily summaries.
Information officer who is able to provide support to optimise sustainability.
FACILTIY HELD PATIENT CARDS